This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1575
Eval/rewards/chosen: 2.5930
Eval/logps/chosen: -116.6651
Eval/rewards/rejected: -10.1233
Eval/logps/rejected: -282.2972
Eval/rewards/margins: 12.7163
Eval/kl: 7.4003

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 200
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.2045	0.8552	100	0.2515	16.7171
0.0457	1.7103	200	0.2056	14.2697
0.0271	2.5655	300	0.1644	9.4286
0.0157	3.4206	400	0.1575	7.4003

Framework versions

Transformers 4.43.0.dev0
Pytorch 2.2.2+cu121
Datasets 2.19.2
Tokenizers 0.19.1

RichardErkhov/stojchet_-_k3-awq

Original model description:

k3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
stojchet_-_k3-awq